Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (3): 820-828.doi: 10.13229/j.cnki.jdxbgxb.20230564

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Eco⁃heating control method for connected electric automotive heat pump system in winter conditions

Xun GONG1(),Hang REN1,Hua-lin ZHANG2,Jie-yu WANG1,Yun-feng HU3,4,Yao SUN3()   

  1. 1.School of Artificial Intelligence，Jilin University，Changchun 130012，China
    2.College of Engineering and Technology，Southwest University，Chongqing 400715，China
    3.National Key Laboratory of Automotive Chassis Integration and Bionics，Jilin University，Changchun 130022，China
    4.College of Communication Engineering，Jilin University，Changchun 130012，China
  • Received:2023-06-05 Online:2025-03-01 Published:2025-05-20
  • Contact: Yao SUN E-mail:gongxun@jlu.edu.cn;syao@jlu.edu.cn

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Abstract:

In response to the "range anxiety" issue of battery electric vehicles caused by cabin heating demands in cold winter climate conditions， the sensitivity relationship between vehicle speed and the energy consumption of a heat pump air conditioning system was explored. A new paradigm of a control-oriented high-precision prediction model for the heat pump air conditioning system was developed. Then，based on this model， the vehicle speed preview information provided in the connected environment was integrated into the design of the thermal management controller， creating a predictive eco-heating strategy （EHS） based on model predictive control （MPC）. The proposed EHS was validated using a high-fidelity physical simulation model based on Dymola. The simulation results show that by utilizing vehicle speed preview information to optimize the operation load of the air conditioning system， while satisfying the thermal comfort requirements， it further achieves a 18.46%-20.61% improvement in energy efficiency compared to the baseline controller.

Key words: control theory and control engineering, heat pump air conditioning, model predictive control, eco-heating

CLC Number: 

  • TP273

Fig.1

Schematic of the heat pump air conditioning system in battery electric vehicles"

Table 1

Design specifications of major components of the heat pump air conditioning system"

元件选型及参数
压缩机EffCompressor模块；涡旋式压缩机；排量为6 cm3；最大转速为100 Hz

气体冷

却器

MPET.MoistAirVLEFluid.DetailedCrossFlowHX模块；多孔扁管平行流换热器；材质为铝；总高度为0.45 m；总宽度为0.60 m；总深度为0.015 m；流体层数为1；每层流程数为2；每个流程管道数为｛30，15｝；每个管道的端口数为19；端口直径为1 mm；扁管厚度为1 mm；翅片厚度为0.08 mm；翅片间距为1.2 mm
回热器TubeInTube.VLEFluid.ParallelFlowHX模块；套管式平行流换热器；材质为铝；总长度为0.65 m；翅片厚度为1.5 mm；平行管道数为10
蒸发器MPET.MoistAirVLEFluid.DetailedCrossFlowHX模块；多孔扁管平行流换热器；材质为铝；总高度为0.30 m；总宽度为0.25 m；总深度为0.04 m；流体层数为2；每层流程数为3；每个流程管道数为｛14，14，14｝；每个管道的端口数为19；端口直径为1 mm；扁管厚度为1.5 mm；翅片厚度为0.1 mm；翅片间距为1.5 mm
膨胀阀OrificeValve模块；电子膨胀阀

Fig.2

P-h diagrams of transcritical cycle"

Fig.3

Vehicle speed sensitivity of heat pump air conditioning system"

Table 2

Energy consumption for each case in the speed sensitivity test"

参数车速/（km·h-1）
020406080100120
能耗/kJ678623512458420396375
节能率/%08.12432384245

每千米能耗/

（kJ·km-1）

—26212985634940

Fig.4

Validation of the predictive model"

Fig.5

Control strategy for the heat pump air conditioning system in battery electric vehicles"

Fig.6

Controller parameters integration of vehicle speed sensitivity in EHS"

Fig.7

Simulation results of MPC-based eco-heating strategy in closed-loop"

Table 4

Simulation results"

工况EHS能耗/kJNMPC能耗/kJ节能率/%
CLTC708.79869.2618.46
UDDS575.19712.0519.22
NEDC595.22749.7020.61
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